COLDBOOT RESEARCH
Independent Mobile Privacy Forensics
contact@coldboot-research.com
Public Interface / Research Surface

We capture what applications transmit before user action begins.

Independent research focused on mobile privacy behavior under zero-interaction conditions. Our workflow combines kernel attribution, TLS session inspection, runtime interception, and artifact integrity controls into a single evidentiary surface.

133+
Applications Assessed
27
S-Class Findings
06
Evidence Layers
[ 01 ] Method Stack
Primary technical capabilities exposed through the public surface.

Kernel visibility. Decrypted payloads. Runtime corroboration.

01 / TLS
Session-key-based TLS inspection
Visibility into TLS 1.2 and 1.3 application traffic through extracted session material, enabling payload-level inspection beyond endpoint metadata and domain classification.
02 / UID
Kernel-level process attribution
Per-flow attribution through Linux networking primitives and application UID correlation, reducing ambiguity around origin process and transmission ownership.
03 / RT
Native runtime interception
Instrumentation of network and identifier-adjacent API surfaces to independently corroborate transmission behavior, parameter access, and outbound write operations.
04 / ZERO
Zero-interaction execution protocol
Controlled launch conditions designed to capture activity occurring before meaningful user participation, interface traversal, or consent pathway engagement.
[ 02 ] Evidence Surface
Layered artifacts intended to stabilize interpretation and preserve reproducibility.

Six evidentiary layers. One coherent chain.

Layer 01
Network Capture
Packet-level collection with deterministic artifact retention and cryptographic manifesting.
Layer 02
TLS Session Material
Session-key-derived visibility into headers, request bodies, serialized fields, and outbound payload structure.
Layer 03
Process Attribution
Kernel-linked correlation between captured network activity and target application execution context.
Layer 04
API Interception
Independent runtime observation of identifier access and transmission-adjacent function behavior.
Layer 05
Local Forensics
Device-state and local-storage capture, including application-resident persistence surfaces relevant to analysis.
Layer 06
Integrity Controls
Artifact hashing, ordered manifests, and timestamp discipline intended to preserve downstream evidentiary coherence.
[ 03 ] Public Research Surface
Public-facing research signals modeled after technical labs and security research interfaces.

Selected research surfaces, expressed as technical notes rather than marketing claims.

Technical Note
Pre-consent transmission analysis across regulated mobile categories
Comparative observation of identifier, session-bootstrap, and analytics-layer transmissions occurring before meaningful user interaction in sensitive application classes.
Method Note
Attribution before interpretation under modern mobile TLS handling
A research stance that treats app-process attribution as a prerequisite for interpretation, rather than inferring source ownership from proxy-only or endpoint-only observation.
Forensic Note
Zero-interaction launch behavior as an evidentiary condition
Controlled execution designed to isolate transmission behavior occurring prior to affirmative choice, interface traversal, onboarding completion, or consent-state mutation.
[ 04 ] Findings Classes
Representative observation classes across mobile privacy analysis.

Observed as classes of behavior, not just isolated packets.

Class 01
Pre-consent identifier transmission
Device- or session-linked values transmitted before users can meaningfully act on interface state or disclosure surfaces.
Class 02
Third-party SDK bootstrap signaling
Early-stage emissions associated with analytics, advertising, attribution, or embedded third-party service initialization.
Class 03
Runtime-access / outbound-write correlation
Observed linkage between identifier access, API interception, and matching outbound transmission pathways.
Class 04
Attribution mismatch in proxy-only analysis
Cases where traffic interpretation without process-level attribution can misstate which application or component emitted the observed data.
[ 05 ] Findings Surface
Representative sectors present in high-severity mobile observations.

Observed across regulated, sensitive, and high-volume mobile sectors.

Health Monitoring Telehealth Insurance Asset Management Tax Preparation International Finance Government Benefits Dating Food Delivery Retail
[ 06 ] Public Contact
Public-facing communications endpoint for confidential technical discussion.

Private detail remains private. Initial contact does not.

This page is a public interface, not a dossier. Detailed target coverage, artifacts, and technical materials are not published here. For private discussion, secure exchange, or scoped review, initiate contact directly.